What
After 6-8 weeks of real usage data, add an intent detection layer so users can describe what they want to do in natural language and the app auto-selects the correct session mode and artifact type.
Scope
- Text input on dashboard: "What do you want to work on?"
- AI classifies intent into one of the 5 modes + artifact type (for create mode)
- Pre-selects mode and artifact type with a confirmation step ("I think you want a Create session for email_sequence — correct?")
- Explicit mode selection remains as permanent override
- Train on historical session data: what modes users actually chose for similar prompts
Reference
SPEC.md Section 5 — Skill Routing, Phase 2. Explicitly out of scope for v1, designed for after real usage validates the mode taxonomy.
What
After 6-8 weeks of real usage data, add an intent detection layer so users can describe what they want to do in natural language and the app auto-selects the correct session mode and artifact type.
Scope
Reference
SPEC.md Section 5 — Skill Routing, Phase 2. Explicitly out of scope for v1, designed for after real usage validates the mode taxonomy.